David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Minds and Machines 5 (4):467-487 (1995)
Heuristics can be regarded as justifying the actions and beliefs of problem-solving agents. I use an analysis of heuristics to argue that a symbiotic relationship exists between traditional epistemology and contemporary artificial intelligence. On one hand, the study of models of problem-solving agents usingquantitative heuristics, for example computer programs, can reveal insight into the understanding of human patterns of epistemic justification by evaluating these models'' performance against human problem-solving. On the other hand,qualitative heuristics embody the justifying ability of defeasible rules, the understanding of which is provided by traditional epistemology.
|Keywords||Heuristics epistemology problem-solving justification defeasible reasoning|
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References found in this work BETA
Alvin I. Goldman (1986). Epistemology and Cognition. Harvard University Press.
Roderick M. Chisholm (1966). Theory of Knowledge. Englewood Cliffs, N.J.,Prentice-Hall.
John Pollock (1987). Defeasible Reasoning. Cognitive Science 11 (4):481-518.
John McCarthy (1980). Circumscription — A Form of Non-Monotonic Reasoning. Artificial Intelligence 13:27–39.
Ray Reiter (1980). A Logic for Default Reasoning. Artificial Intelligence 13:81-137.
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